activity
20192022
most citedDon't Judge a Language Model by Its Last Layer: Contrastive Learning with Layer-Wise Attention Pooling

5 citations · 5 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20225 cited

Don't Judge a Language Model by Its Last Layer: Contrastive Learning with Layer-Wise Attention Pooling

Dongsuk Oh, Yejin Kim, Hodong Lee +2

Recent pre-trained language models (PLMs) achieved great success on many natural language processing tasks through learning linguistic features and contextualized sentence represen…

cs.CL2020

I Know What You Asked: Graph Path Learning using AMR for Commonsense Reasoning

Jungwoo Lim, Dongsuk Oh, Yoonna Jang +2

CommonsenseQA is a task in which a correct answer is predicted through commonsense reasoning with pre-defined knowledge. Most previous works have aimed to improve the performance w…

cs.CL2020

Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection

Taesun Whang, Dongyub Lee, Dongsuk Oh +4

In this paper, we study the task of selecting the optimal response given a user and system utterance history in retrieval-based multi-turn dialog systems. Recently, pre-trained lan…

cs.CL2019

Word Sense Disambiguation using Knowledge-based Word Similarity

Sunjae Kwon, Dongsuk Oh, Youngjoong Ko

In natural language processing, word-sense disambiguation (WSD) is an open problem concerned with identifying the correct sense of words in a particular context. To address this pr…

cs.CL2019

An Effective Domain Adaptive Post-Training Method for BERT in Response Selection

Taesun Whang, Dongyub Lee, Chanhee Lee +3

We focus on multi-turn response selection in a retrieval-based dialog system. In this paper, we utilize the powerful pre-trained language model Bi-directional Encoder Representatio…